Breaking Linear Classifiers on ImageNet

1 · Andrej · March 30, 2015, 8 p.m.
You’ve probably heard that Convolutional Networks work very well in practice and across a wide range of visual recognition problems. You may have also read articles and papers that claim to reach a near “human-level performance”. There are all kinds of caveats to that (e.g. see my G+ post on Human Accuracy is not a point, it lives on a tradeoff curve), but that is not the point of this post. I do think that these systems now work extremely well across many visual recognition tasks, especially on...